Tumor-infiltrating lymphocyte (TIL) therapy in adoptive T-cell therapy (ACT) has already caused durable regression in a variety of cancer types due to T-cell persistence, clinical activity, and duration of objective response and safety. TILs are composed of polyclonal effector T-cells specific to heterogenetic tumor antigens, reasonably providing a promising means for tumor therapy. In addition, their expansion in vitro can release them from the suppressive tumor microenvironment. Even though significant advances have been made in the procedure of TIL therapy, from TIL isolation, modification, expansion, and infusion back to the patient to target the tumor, strategy optimization is always ongoing to overcome drawbacks such as a complex process, options for the lineage differentiation status of TILs, and sufficient trafficking of TILs to the tumor. In this review, we summarize the current advances of TIL therapy, raise problem-based optimization strategies, and provide future perspectives on next-generation TIL therapy as a potential avenue for enhancing cell-based immunotherapy.

Lung adenocarcinoma (LUAD) is the most common type of lung cancer and the leading cause of cancer incidence and mortality worldwide. Despite the improvement of traditional and immunological therapies, the clinical outcome of LUAD is still far from satisfactory. Patients given the same treatment regimen had different responses and clinical outcomes due to the heterogeneity of LUAD. How to identify the targets based on heterogeneity analysis is crucial for treatment strategies. Recently, the single-cell RNA-sequencing (scRNA-seq) technology has been used to investigate the tumor microenvironment (TME) based on cell-specific changes and shows prominently valuable for biomarker prediction. In this study, we systematically analyzed a meta-dataset from the multiple LUAD scRNA-seq datasets in LUAD, identified 15 main types of cells and 57 cell subgroups, and revealed a series of potential biomarkers in M2b, exhausted CD8⁺T, endothelial cells, fibroblast, and metabolic patterns in TME, which further validated with immunofluorescence in clinical cohorts of LUAD. In the prognosis analysis, M0 macrophage and T cell activation were shown correlated to a better prognosis (p<0.05). Briefly, our study provided insights into the heterogeneity of LUAD and assisted in novel therapeutic strategies for clinical outcome improvement.

This study aimed to evaluate the diagnostic value of chemiluminescence immunoassay (CLIA), passive particle agglutination (PPA), and indirect immunofluorescence assay (IFA) in detecting Mycoplasma pneumoniae infection in children. Serum samples from 165 children with acute community-acquired respiratory tract infections were examined using CLIA, PPA, and IFA, and consistency coefficient, specificity, and sensitivity were analyzed. Compared with the PPA (titer ≥ 1:160), the consistency coefficients of the immunoglobulin(Ig)M-CLIA, immunoglobulin(Ig)G-CLIA and IgM-IFA methods were 93.94%, 75.76%, and 83.64%, respectively. The positive likelihood ratio (PLR) and specificity of IgM-CLIA was 19.40 and 95.49%, respectively. The consistency coefficient of (IgM+IgG)-CLIA and PPA (titer ≥ 1:160) was 89.1%, and the sensitivity and negative predictive value of (IgM+IgG)-CLIA were 96.88% and 98.94%, respectively. CLIA MP-IgM has high concordance with PPA, and its specificity and sensitivity are higher than those of CLIA MP-IgG and IFA MP-IgM, suggesting its better diagnosis of early MP infection. The sensitivity and negative predictive value of CLIA MP (IgM+IgG) were higher than those of PPA or IFA, indicating that it should be considered as a priority in the diagnosis of MP infection.

Background Prognostic indicators in lung adenocarcinoma (LUAD) have been seeking under database analysis, and remarkable advance is on the way. Methods This study calculated the scores of stromal and immune components of the tumor microenvironment (TME) in 551 LUAD samples using the ESTIMATE algorithm on The Cancer Genome Atlas (TCGA) database. R package ''limma'' was used to selected differentially expressed genes (DEG). We have analyzed the DEGs by means of Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichments. The protein‐protein network, univariate Cox analysis, and Lasso regression analysis were performed to selected survival‐related genes. Gene Set Enrichment Analysis (GSEA) represented the enriched pathway of CC chemokine receptor 2 (CCR2). The ratios of immune cells in the TME of each LUAD sample were obtained using the R package "limma" and CIBERSORT algorithm in R 4.0.2. Results The ImmuneScore was positively correlated with prognosis regarding survival rate, T classification of TNM stages, and clinicopathological staging characteristics. GO and KEGG enrichments showed DEGs were associated with immune‐related activities. Three genes of LUAD were selected from the PPI network and Cox proportional hazards regression analysis. CCR2 was the most survival correlated gene by Lasso regression analysis. GSEA results showed that C2 kegg gene sets in the CCR2 high‐expression group were mainly enriched in the B cell or T cell receptor signaling pathway and natural killer cell‐mediated cytotoxicity. Correlation of CCR2 expression with prognosis was conducted, implicating a positive correlation with the prognosis of survival rate and M classification, negative correlation with the prognosis of T and N classifications. The correlation between CCR2 and tumor‐infiltrating immune cells (TICs) was analyzed, and 14 kinds of TICs were found closely correlated with CCR2 expression through difference analysis. Conclusion Therefore, CCR2 has prognostic value as an immune indicator in LUAD.

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